Name: rnai-mediated control of aflatoxins in peanut: method to analyze mycotoxin production and transgene expression in the peanut/aspergillus pathosystem
Uploaded: 2015-12-21T14:00:00
Duration: 9 min 44 s
Description: Watch this Scientific Journal Video about RNAi-mediated Control of Aflatoxins in Peanut: Method to Analyze Mycotoxin Production and Transgene Expression in the Peanut/Aspergillus Pathosystem at JoVE.c

This work received the financial support of USDA-ARS CRIS project 6604-21000-004-00D, CRIS project 6604-42000-008-00D, and USAID Feed-the-Future program Agreement number 58-0210-3-012. We thank Valerie Orner, LaTanya Johnson, Joseph Powell and Kathy Gray for their technical assistance. Mention of trade names or commercial products in this article is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the US Department of Agriculture.

1. Molecular Construct and Peanut Transformation
<ol>
	<li>Combine DNA fragments of five A. flavus genes, AFL2G_07223 (aflS or aflJ), AFL2G_07224 (aflR), AFL2G_07228 (aflC/pksA/pksL1), AFL2G_07731 (pes1) and AFL2G_05027 (aflatoxin efflux pump, aflep). For this, use the following primers and ultramers: DIR-1, Short-Dir1-R, DIR-2-inverted, Short-Dir2-R, DirAll-Nco-Rv, and DirAll-BamEco-Fw, Table 1.
	<ol>
		<li>Make DIR-1 double strand by 5 PCR cycles (25 &#956;l reaction; 95 &#176;C 2 min, followed by 5 cycles of 94 &#176;C 45 sec, 55 &#176;C 30 sec, 68 &#176;C 15 sec) using DNA polymerase according to manufacturer&#39;s instructions and primer Short-Dir1-R to leave a 3&#39; overhang CCCGT. Repeat these steps to make DIR-2-inverted double strand using primer Short-Dir2-R to leave a 3&#39; overhang ACGGG complementary to DIR-1.</li>
		<li>Ligate the two 199 bp fragments with T4 DNA Ligase as per manufacturer&#39;s instructions. PCR amplify the resulting 393 bp fragment as indicated in 1.1.1 using primers DirAll-cacc-Fw and DirAll-Nco-Rv (Table 1), and clone the product using standard techniques into pENTR1A to make plasmid p2+4ENTR.</li>
		<li>Recombine p2+4ENTR into pCAPD 29 (NCBI Accession: KC176455.1) using LR clonase II enzyme mix according to manufacturer&#39;s instructions to make plasmid p5XCAPD, and transform it into Escherichia coli DH5&#945; using standard techniques followed by partial sequencing. Note: The complete RNAi insert is shown in Table 1.</li>
	</ol>
	</li>
	<li>Transform Agrobacterium strain C58C1 30 with plasmid p5XCAPD as previously reported30, and use the resulting bacterium to transform peanut plants as follows:
	<ol>
		<li>Grow at 30 &#176;C the Agrobacterium harboring p5XCAPD, use for this, 50 ml LB-Broth supplemented with 500 &#956;g ml-1 streptomycin, 25 &#956;g ml-1 gentamicin, 10 &#956;g ml-1 kanamycin, and shake the culture at 250 rpm until reaching 1 OD260.</li>
		<li>Harvest the Agrobacterium cells by centrifugation (6,000 x g) for 10 min, resuspend in 50 ml AB minimal medium 31 with 100 &#956;M acetosyringone for 1 hr, and place in the bacterial suspension the explants from 10-14 day old seedlings Exp27-1516, runner-type peanut breeding line. Blot dry the explants on 3MM blotting paper after 30 min, and place them on shoot-induction medium (SIM) [MS salt 32, 3% sucrose, 20 &#956;M benzylaminopurine (BAP), 10 &#956;M thidiazuron (TDZ), pH 5.8, 0.3% gellan gum] without antibiotics in the dark for three days.</li>
		<li>Do tissue selection and regeneration as reported before 33. Move tissues to SIM (500 &#956;M cefotaxime and 100 &#956;M kanamycin) for shoot formation, with bi-weekly transfers for 2 months. Then place expanding shoots on shoot-elongation medium (SEM) [5 &#956;M BAP, 1 &#956;M gibberellic acid (GA3)], bi-weekly for several months.</li>
		<li>Place individual shoots, 2 cm in size, in root-induction medium (RIM) [1/2 MS, 1.5% sucrose, 5 &#956;M &#945;-naphthalene-acetic acid (NAA), 2.5 &#956;M indole-butyric acid (IBA)], then acclimate the seedlings and transfer them to the greenhouse.</li>
	</ol>
	</li>
</ol>
2. Identification of Peanut Plants Harboring RNAi to Silence Aflatoxin Synthesis Genes
<ol>
	<li>Use plant mini kit in a robot workstation with 200 &#956;l elution according to manufacturer&#39;s instructions to extract DNA from young leaves of peanut plants that were subject to the process of transformation (as previously described) with RNAi construct p5XCAPD (Figure 1) which has as backbone plasmid pCAPD 29 for gene silencing.</li>
	<li>Screen the DNA samples by single-tube nested PCR (STN-PCR) as described previously 34 to detect the selectable marker NPTII and the RNAi insert from p5XCAPD. Clonally propagate from cuts (3-4 nodes) PCR positive plants to produce sufficient seeds for testing in this first generation.
	<ol>
		<li>Use four 2-fold dilutions of DNA (50-100 ng &#956;l-1 before dilution) in all STN-PCR reactions. For NPTII, use external primers PCAPD 5714F: 5&#39;-AGGCTATTCGGCTATGACTG-3&#39; and PCAPD 6446R: 5&#39;-CGTCAAGAAGGCGATAGAAG-3&#39;, and internal primers PCAPD 5730F: 5&#39;-ACTGGGCACAACAGACAATC-3&#39; and PCAPD 6249R: 5&#39;-ATATTCGGCAAGCAGGCATC-3&#39;.</li>
		<li>For detection of RNAi insert in STN-PCR reactions use external primers 35S-PDSFw: 5&#39;-CCTAACAGAACTCGCCGTAA-3&#39; and DirAll-Nco-Rv: 5&#39;-ATGCCATGGGGTTATTGGGTGCAGAATGG-3&#39;, and internal primers Probe_5027_Fw: 5&#39;-gtatttgtgaccatgtttctg-3&#39; and Probe_7228_Rv: 5&#39;-GGACGGATAGTAAACTGCGG-3&#39;.</li>
	</ol>
	</li>
	<li>Harvest peanut pods from STN-PCR positive plants and of the control plants grown in the same conditions. CRITICAL STEP: Ensure that control plants are grown in the same conditions and the same season as the RNAi plants. Water blast the pods with a pressure washer at low intensity or scrape by hand to remove exocarp, determine the color of the mesocarp by placing the pods on a maturity board and separate pods in groups (yellow, orange, brown and black) 35 (Figure 2).</li>
</ol>
<img alt="Figure 2" src="/files/ftp_upload/53398/53398fig2.jpg" /> 
Figure 2. Preparation of peanut pods for analysis.&#160; Left: Different peanut sizes found at harvest as peanut is an indeterminate growth plant; Center: placing peanuts in metal basket for water pressure removal of exocarp; Right: maturity groups by mesocarp color on a peanut profile board (yellow, orange, brown and black). <a href="https://www.jove.com/files/ftp_upload/53398/53398fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
3. Experimental Setup
<ol>
	<li>Remove the hulls, process yellow and brown seeds separately. Calculate the number of seeds to use in the experiment according to Table 2. Note that a minimum of three seed pieces (1 seed piece = half cotyledon) per peanut line and sampling date is required to perform statistical analysis and reduce the standard error.</li>
</ol>
<table fo:keep-together.within-page="1">
	<tbody>
		<tr height="33">
			<td height="33" style="height:33px;width:147px;">Name</td>
			<td colspan="3" style="width:421px;">Sequence&#160;</td>
		</tr>
		<tr height="124">
			<td height="124" style="height:124px;">DIR-1</td>
			<td colspan="3" style="width:421px;">5&#39;- 
			GCCAGCTCAAAAGTGCGATGCACCAAGGAGAAACCGGCCTGTGCT 
			CGGTGTATCGAACGTGGTCTTGCCTGTCAATACATGGTCGTATTTG 
			TGACCATGTTTCTGGTGGCATTGGACCGTCTTGTCATCTCTACAGCC 
			ATTCCCCAGATCACGGACGAATCCCCTGCATCTACGCGCACGCATC 
			ACTTGGGGTACCCGT-3&#39;</td>
		</tr>
		<tr height="24">
			<td height="24" style="height:24px;">Short-Dir1-R</td>
			<td colspan="3" style="width:421px;">5&#39;-Phos-TACCCCAAGTGATGCGTGCGCG-3&#39;</td>
		</tr>
		<tr height="126">
			<td height="126" style="height:126px;">DIR-2-inverted</td>
			<td colspan="3" style="width:421px;">5&#39;- GGTTATTGGGTGCAGAATGGTAAACCACCCAACAGTACGCGAAATG 
			TCAATTCCAGAGTCCCAAACCTCCCTACCGTGGCCTGGACGGATAG 
			TAAACTGCGGAGCTTGGGAACAAAATCCGCTGTCTGATCGCCGAAG 
			AGAAAGAGTTGCCTTGATTGAGCCGCATCGAGGACAGGTTGTGTTG 
			CTGTTGATAGACGGG-3&#39;</td>
		</tr>
		<tr height="29">
			<td height="29" style="height:29px;">Short-Dir2-R</td>
			<td colspan="3" style="width:421px;">5&#39;-Phos-CTATCAACAGCAACACAACC-3&#39;</td>
		</tr>
		<tr height="30">
			<td height="30" style="height:30px;">DirAll-cacc-Fw</td>
			<td colspan="3" style="width:421px;">5&#39;-CACCGCCAGCTCAAAAGTGCGATGC-3&#39;</td>
		</tr>
		<tr height="24">
			<td height="24" style="height:24px;">DirAll-Nco-Rv</td>
			<td colspan="3">5&#39;-ATGCCATGGGGTTATTGGGTGCAGAATGG-3&#39;</td>
		</tr>
		<tr height="24">
			<td height="24" style="height:24px;">DirAll-BamEco-Fw</td>
			<td colspan="3" style="width:421px;">5&#39;-ATGGGATCCGAATTCGCCAGCTCAAAAGTGCGATGC-3&#39;</td>
		</tr>
		<tr height="197">
			<td height="197" style="height:197px;">Complete RNAi insert</td>
			<td colspan="3" style="width:421px;">5&#8217;- GCCAGCTCAAAAGTGCGATGCACCAAGGAGAAACCGGCCTGTGCT 
			CGGTGTATCGAACGTGGTCTTGCCTGTCAATACATGGTC/GTATTTG 
			TGACCATGTTTCTGGTGGCATTGGACCGTCTTGTCATCTCTACAGCC 
			ATTCCCCAGATCACGGACGAAT/CCCCTGCATCTACGCGCACGCAT 
			CACTTGGGGTACCCGTCTATCAACAGCAACACAACCTGTCCTCGAT 
			GCG/GCTCAATCAAGGCAACTCTTTCTCTTCGGCGATCAGACAGCG 
			GATTTTGTTCCCAAGCTCCGCAGTTTACTATCCGTCCA/GGCCACGG 
			TAGGGAGGTTTGGGACTCTGGAATTGACATTTCGCGTACTGTTGGG 
			TGGTTTACCATTCTGCACCCAATAACC-3&#8217;</td>
		</tr>
	</tbody>
</table>
Table 1. Oligonucleotides and ultramers used to build the RNAi construct p5XCAPD. Phos: phosphorylated 5&#8217; end; &#8220;/&#8221; separates the five gene fragments used; Complete RNAi insert: sequence used as 2 inverted repeats to form p5XCAPD.
<ol start="2">
	<li>Place entire peanut seeds in a single layer so that they cover the bottom of a sterile beaker.&#160; Add 75% ethanol/water (v/v) solution to cover the seeds and then add an equal volume of the same solution.&#160; Incubate at ambient temperature for 30 sec and then rinse with sterile deionized water (SDW).</li>
	<li>Add 2% hypochlorite to the beaker containing the ethanol treated seeds as follows: add enough 2% hypochlorite solution to cover the seeds, then add an equal volume of the same solution and incubate for 5 min. CRITICAL STEP: Rinse thoroughly three times with a volume of SDW equivalent to 5-fold the volume of hypochlorite used (Figure 3).</li>
</ol>
<img alt="Figure 3" src="/files/ftp_upload/53398/53398fig3.jpg" /> 
Figure 3. Experimental setup. Top: Surface sterilization of peanut seeds before and after hypochlorite, removal of seed coats (testa); Middle: removal of embryo and close view of embryo, then cut cotyledon in half; Bottom: half cotyledons in sterile distilled water, blotting on sterile absorbent paper, dents on water agar, and placing of half cotyledons (cut side upwards) on the agar surface. <a href="https://www.jove.com/files/ftp_upload/53398/53398fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<ol start="4">
	<li>Allow the surface-sterilized seeds to imbibe submerged in SDW for 2 hr. Place the seeds on a sterile Petri dish, remove the seed coats with forceps, separate the cotyledons, and with a scalpel remove the embryos. Note: Embryos can be discarded or used to regenerate new plants.</li>
	<li>Cut each cotyledon in half using a scalpel. To avoid dehydration, keep the cut seed pieces in sterile water until all the seeds are processed.</li>
	<li>Have prepared Petri dishes containing sterile water agar (1.5% agar/water; w/v), one for each three seed pieces. Make small dents in the agar using forceps, briefly blot the excess water of seed pieces on sterile paper towels, and then place the seed pieces (cut face upwards) on the water/agar plates.</li>
	<li>From a fresh culture of aflatoxigenic Aspergillus flavus NRRL 3357 in Czapek&#39;s agar medium grown at 25 &#176;C for 10 days, prepare a suspension of 50,000 spores per &#956;l SDW, counted with a haemocytometer.</li>
	<li>Place 2 &#956;l of the spore suspension on the cut surfaces of each half-cotyledon piece avoiding runoff on the sides, to make sure the spores get exposed to the seed tissue that harbors RNAi (Figure 4).</li>
</ol>
<img alt="Figure 4" src="/files/ftp_upload/53398/53398fig4.jpg" /> 
Figure 4. Inoculation and incubation for aflatoxin analysis. Top: Half cotyledon, inoculation with spore suspension, and Aspergillus flavus mycelial growth on half cotyledon after 24 hr incubation.&#160; Bottom:&#160; left: incubation of 48 hr on 1.5% agar; center: incubation for 72 hr on 1.5% agar; right: example of incorrect experimental setup, incubation for 72 hr on 0.5% agar. &#160; <a href="https://www.jove.com/files/ftp_upload/53398/53398fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<ol start="9">
	<li>Incubate the Petri dishes containing inoculated and non-inoculated half cotyledons at 30 &#176;C in the dark until sampling.</li>
</ol>
4. Sampling for Aflatoxin Analysis and Gene Expression
<ol>
	<li>Collect samples in triplicate at 24, 48 and 72 hr (optional 96 hr) of incubation, both for RT-PCR and for aflatoxin analysis, each replicate being one piece (half cotyledon). Pick samples at random from different plates on each sampling date. Using a tissue, softly remove agar and excess fungal spores before placing seed pieces in vials or test tubes.</li>
	<li>For aflatoxin analysis, place each replicate (one piece) in a 4 ml glass screw cap vial and store at -80 &#176;C. Note: Given the chemical stability of aflatoxins, samples can be stored in this condition for several months (in the current experiments usually 1-2 months).</li>
	<li>For RT-PCR place each replicate (one piece) in already prepared 2 ml grinding tubes containing two stainless steel beads (2.5 mm diam) and three zirconium beads (2 mm diam).</li>
	<li>Immediately freeze (preferably in liquid nitrogen) all the samples and keep them at -80 &#176;C until processing.</li>
</ol>
5. Aflatoxin Analysis of Individual Half Cotyledon Pieces
<ol>
	<li>Use the A. flavus inoculated samples for this analysis. Bring samples to ambient temperature for about 30 min, add four volumes (usually 2-3 ml; w/v) of methanol (keep record for later calculations), close the caps, and incubate O/N (~16 hr) in the dark without agitation.</li>
	<li>Place a frit into a matching 1.5 ml propylene minicolumn, add 200 mg basic Al2O3 and cap it with another frit as described previously 36; then, place an Ultra-High Performance Liquid Chomatographer (UPLC) autosampler vial under the column close enough to avoid possible evaporation of the eluate.</li>
	<li>In a disposable glass test tube (do not use plastic), place 0.5 ml of the methanol extract obtained in step 4.1, add 0.5 ml acetonitrile, mix by pipette and apply 0.5 ml of the mixture into the column prepared in step 4.2. Allow elution into the autosampler vial by gravity (do not apply pressure). Elution usually takes 2-4 min, close the vial immediately using a UPLC compatible cap with septa. Keep the vials at ambient temperature and analyze them the same day on a UPLC.</li>
	<li>For separation of aflatoxins, place autosampler vials containing sample eluates and autosampler vials with aflatoxin standards (B1 and B2 when using A. flavus) in a UPLC instrument equipped with a matching UPLC Quaternary Solvent Manager, UPLC Sample Manager, UPLC Fluorescent Detector, and an C18 2.1 mm x 50 mm, 1.7 &#181;m column.
	<ol>
		<li>Use an isocratic mobile phase composed of water/MeOH/CH3CN (64:23:13, v/v/v) mixture at the flow rate of 0.30 ml min-1. Obtain chromatograms assuring a stabilized baseline separation for accurate calculation of aflatoxin concentration, according to manufacturer&#39;s instructions 37.</li>
		<li>Confirm the identity of aflatoxins by obtaining their mass-spectral data and comparing them with published data 38. Use an ion trap mass spectrometer equipped with an ESI interface and corresponding software according to manufacturer&#39;s instructions.</li>
	</ol>
	</li>
	<li>Determine concentrations of aflatoxins by reference to calibration curves obtained by injecting different amounts of corresponding commercial standards of aflatoxins B1, B2, G1 and G2 as suggested by the UPLC manufacturer and determined by the software 37.</li>
	<li>Place seed pieces already extracted with methanol, in individual glass vials for O/N (~16 hr) lyophilization to determine their dry weight. Then, calculate aflatoxin concentration in ng.g-1 of dry weight of seed piece.</li>
	<li>For analysis of data, convert aflatoxin results to log (ng.g-1 +1), followed by Tukey&#39;s test for mean comparisons.</li>
</ol>
6. Gene Expression, RT-PCR Processing of Samples
<ol>
	<li>Take the 2 ml grinding tubes containing samples from the -80 &#176;C freezer, and immediately (without thawing) grind them in a bead mill homogenizer at 3,100 rpm for 40 sec, then proceed to RNA extraction using Trizol according to manufacturer&#39;s instructions.</li>
	<li>Prepare cDNA from each sample using 1 &#956;g RNA and equal amounts of oligo dT and random hexamers, make a 1:8 dilution of the cDNA and use 2 &#956;l per reaction in RT-PCR (as previously described 39).
	<ol>
		<li>For detection of expression of RNAi insert use primers: RT_5X_1_105F: 5&#39;GGTGGCATTGGACCGTCTTG-3&#39;, RT_5X_1_232R: 5&#39;-CGCATCGAGGACAGGTTGTG-3&#39;; and RT_5X_2_95F: 5&#39;-CCATGTTTCTGGTGGCATTG-3&#39;, RT_5X_2_229R: 5&#39;-ATCGAGGACAGGTTGTGTTG-3&#39;.</li>
		<li>For detection of expression of the selectable marker NPTII, use primers: RT_NPTII_1_6871F: 5&#39;-CTCGCTCGATGCGATGTTTC-3&#39;, RT_NPTII_1_7004R: 5&#39;-GCAGGATCTCCTGTCATCTC-3&#39;. Use the housekeeping gene Actin for standardization, and primers: Actin-Fw: CACATGCCATCCTTCGATTG; Actin-Rv: CCAAGGCAACATATGCAAGCT 40.</li>
	</ol>
	</li>
	<li>Analyze results by Delta-delta CT method 41 standardized for Actin expression. Represent the results as fold increase over the control.</li>
</ol>

The authors have nothing to disclose or any conflicts of interest.

Plant-host RNAi-mediated silencing of genes in fungal pathogens has been demonstrated 27,43, however, there are no publications showing the feasibility of RNAi-mediated control of mycotoxin accumulation in plants. One limiting factor for these studies in peanut was the lack of a method to evaluate a no-aflatoxin accumulation phenotype in individual plants, as leaves show no symptoms upon fungal infection of underground pods. In addition, the not-normally distributed accumulation of aflatoxins, and the need for large samples for chemical analysis 15,16 have hindered the quantification of potential RNAi effect on a single plant. The method presented here consists of 72 hr experiments using five seeds to perform three 24 hr-interval samplings in triplicate (Table 1, Figure 7). Compared to the typical aflatoxin analysis that requires no less than 100 g of seeds, our method is particularly suitable for individual transgenic events of peanut plants which initially produce no more than two or three pods.
RNA-mediated silencing of aflatoxin synthesis has been demonstrated by genetically transforming Aspergillus flavus and A. parasiticus. Since aflR is a main regulator of aflatoxin production in A. flavus and A. parasiticus44,45, it becomes an interesting target for RNA-mediated silencing in plants. However, genetic variations in aflR have been shown among Aspergillus species 46, and those genetic variants could escape silencing if there is no perfect sequence matching with the RNAi signal produced in the plant host. Thus, aflR was one of the targets for silencing in vector p5XCAPD, but was not the only one. Inverted repeats of the aflR gene introduced into A. flavus and A. parasiticus by transformation resulted in silencing and minimal or no production of aflatoxins 47(McDonald et al., 2005b). Also, silencing aflD gene prevented aflatoxin production by up to 98% in A. flavus and A. parasiticus in direct transformation 48. To increase the probability of success in our system, peanut was transformed with inverted repeat fragments of five genes involved in aflatoxin production in A. flavus. Here it is shown that using p5XCAPD that targets for silencing several genes in the aflatoxin synthesis pathway, 90%-100% lower levels of aflatoxin B1 and B2 were achieved in line 288-72, and 60-100% lower levels accumulated in line 288-74 compared to the control, when half cotyledons were inoculated with A. flavus, Figures 4, 7. Most importantly, this method detected statistically significant differences in aflatoxin accumulation by lines 288-72, 288-74 vs. the control throughout the experiment by applying parametric statistics, Figure 7. Given the small sample size, it is important to highlight the need for using a powerful method to detect aflatoxins, these experiments were analyzed by UPLC which has a high resolution, five-fold higher performance and three times higher sensitivity than HPLC 49.
Expression of the RNAi insert in 288-74 was only detected in immature cotyledons (yellow) at 24 hr incubation. The RNAi insert was not detected by RT-PCR on mature cotyledons of 288-74 at 24 hr, or on any maturity group at 48 hr, Figure 6. This same phenomenon was observed in other RNAi transgenic peanut lines (Arias, R.S., 2015 unpublished), where usually RNAi transcripts were only detected on immature cotyledons at 24 hr. RNA samples were treated with DNAse before cDNA synthesis, data were normalized to the level of Actin expression and no evidence of DNA contamination was observed. Should DNA have been present in the samples, it should have been detected in the 48 hr samples as well, but consistently that was not the case. Expression under the control of the 35S-promoter is not always uniform; it can be affected by environmental conditions 50, type of tissue and developmental stage 51,52. At the same time, in the pathway of RNA interference, the rate of mRNA decay and the rate of siRNA decay can vary significantly 53. It is possible that the rapid degradation of the mRNA by the mechanism of RNA interference could have prevented mRNA detection at 48 hr incubation. Whether absence of expression at 48 hr was due to low 35S-promoter driven transcription, or to fast degradation of dsRNA by Dicer remains to be answered. Thus, detection of small RNAs by high throughput sequencing would give a better insight on the processes taking place through RNAi 54 in these experiments. However, since RNA silencing spreads systemically, mainly through the phloem from photosynthate sources to sucrose sinks (in this case peanut seeds) 55, the silencing of aflatoxin-synthesis can occur in seeds without local expression of the RNAi insert. Much research remains to be done to determine the threshold level of small interfering RNAs (siRNAs) necessary to prevent aflatoxin accumulation in seeds. It is important to emphasize the fact that both, mRNA expression of the RNAi construct (Figure 6), and accumulation of aflatoxins B1 and B2 (Figure 7) showed different results for immature (yellow) vs. mature (brown) cotyledons. Peanut plants have indeterminate growth, that is, they present at harvest a range of maturity pods, Figure 2. In addition, seeds from different maturity groups differ in their chemical composition, e.g., 2.4% sucrose in immature seeds, and 1.9% in mature seeds under the same field conditions 56,57. Thus, to understand the actual efficiency of RNA-mediated control of aflatoxin accumulation, it is important to analyze maturity groups separately.
A natural defense of peanut seeds is the production of phytoalexins, which varies in the diversity of compounds produced and their relative quantities depending on the maturity of the seeds and environmental conditions 58-61, and it is particularly higher in embryos compared to cotyledons 62. Embryos also have significantly higher concentrations of nucleic acids, both DNA and RNA than the cotyledons (Arias R.S., unpublished). As peanut seeds mature, changes in their physiology and chemical composition occur 63. Phenolic antioxidants in peanut testa form condensed tannins with fungistatic activity 64; this is also evident in the mesocarp color that reflects maturity stages, yellow to black 35, as its content of tannins and phenolic compounds increases with maturity 65. Thus, presence of testa or embryos in the experiment, given their antimicrobial properties, could have limited fungal growth and therefore overestimated the effect of RNAi silencing, therefore, they were removed. Also, removal of testa and embryos helps limit the sources of variation in the analysis, as the half cotyledon that carries the embryo will have more phytoalexins and more RNA content.
In addition to the analysis by maturity groups and removal of testa and embryo in these experiments, it is important to point out few more observations: a) though results are shown for up to 96 hr incubation, it is recommended to use no more than 72 hr to obtain consistent results, as seeds get degraded by 96 hr; and b) whereas half cotyledons from the same seed, though sampled at random, do not constitute perfectly independent samples, RT-PCR and aflatoxin accumulation within transgenic events showed minimum variation between seeds. Also, an accurate fungal spore count, inoculum volumes of 2 &#956;l, and application of spores on the cut surface of the cotyledons avoiding dripping on the sides are important to make sure the germinated spores are exposed to the plant tissue. The water/agar on the plates should be at 1.5% (w/v), softer agar causes runoff of spores as shown on the last frame of Figure 4 (bottom). Should seed availability from a particular transgenic event be limited, sampling can be done in duplicate instead of triplicate obtaining similar results (i.e., Figure 7); however, triplicate samples will help reduce the standard error. The only limitation of this method is that it requires a highly sensitive system (UPLC) for aflatoxin detection/quantification, but at the same time this reduces the probability of overestimating the effect of RNAi should aflatoxins not be detected by less sensitive methods.
In conclusion, this method offers for the first time a reliable approach to study the effect of RNAi in the control of aflatoxins. Reducing the time for an experiment from an entire cropping season to less than one week, this method will tremendously accelerate the research on RNAi-peanut/Aspergillus pathosystem towards the mitigation and/or elimination of aflatoxins.

Approximately 4.5 billion people are chronically exposed to aflatoxins 1, the most powerful carcinogens known in nature 2. These mycotoxins contaminate 25% of the food crops in the world 3, including maize, cassava, rice, nuts, cereals and spices. 4. Aflatoxins cause stunting in children 5, impair the immune system 6, are present in 58% of hepatocellular-carcinomas in human biopsies 7,8, and kill hundreds of people during periodic outbreaks of aflatoxicosis 9,10. Aflatoxins are polyketide-derived mycotoxins normally produced by Aspergillus flavus and A. parasiticus; aflatoxins B1 and B2 are produced by A. flavus, whereas A. parasiticus also produces G1 and G2. The chemical structure of these compounds and a chromatogram showing their separation by UPLC are shown in Figure 1. 
<img alt="Figure 1" src="/files/ftp_upload/53398/53398fig1.jpg" /> 
Figure 1. Aflatoxins and RNAi insert. Top: chemical structure (left) and example of chromatogram (right) of the four most common polyketide-derived aflatoxins: B1, B2, G1 and G2, produced by Aspergillus parasiticus, A. flavus produces B1 and B2. Bottom: Schematic of gene fragments in the RNAi construct p5XCAPD used for peanut transformation, numbers under arrows are gene-fragment accession numbers in the Aspergillus flavus genome; PIV2: potato intron; bp: base pairs; RT_5X_1 and RT_5X_2: Real-Time PCR primer sites. <a href="https://www.jove.com/files/ftp_upload/53398/53398fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Economic losses in exports due to aflatoxins in peanut alone exceed $450 million U.S. dollars if calculated based on the 4 ng.g-1 limit of aflatoxin allowed for human consumption in the European Union 11. Aflatoxins have been known for 60 years 12; however, though many agricultural practices were developed to mitigate their effect, including application of other fungal strains 13,14, no consistent method of control exists, and resistant plant varieties are not available. Testing plant germplasm for resistance to aflatoxins is particularly difficult, because even under conducive conditions for pathogen invasion, mycotoxin accumulation is unpredictable and does not follow a normal distribution. Thus, experiments usually require large planting areas, hundreds of seeds and multiple samples of 100-1,700 g to reduce variability of the data 15,16.
RNA interference was discovered in 1998 17; and the benefits of &#34;silencing&#34; are currently being explored in a number of new applications, e.g., in human therapies against metastatic breast cancer 18, liver cancer 19, myeloid leukemia 20, and in plant protection against insects 21 and nematodes 22. In plants, RNA interference signals can travel cell to cell, with small interfering RNA (siRNA) and high molecular weight RNA being responsible for the systemic posttranscriptional gene silencing 23,24, even inside fungal pathogens that are in close contact with plant host 25. The effectiveness of RNAi on plant-mediated silencing of fungal-pathogen genes has been described in few plant pathosystems, for these, visual examination of symptoms in the aerial parts of the plants (leaves) allowed disease quantification, i.e., oomycete Bremia in lettuce 26, Puccinia in wheat 27 and Fusarium in banana 28. Much more difficult is to evaluate RNAi effectiveness to control mycotoxins in plants, particularly aflatoxins in peanuts as the leaves show no symptoms of infection, the organs invaded (seeds) are under several inches of soil, the occurrence of infection is unpredictable, and only chemical analysis can determine the presence of aflatoxins. In addition, each transgenic event in peanut normally produces few seeds (4-6 per plant); therefore, traditional testing for a no-aflatoxin accumulation trait in large field plots, lasting entire cropping seasons, and using hundreds of seeds is not feasible. A method is described here to analyze in less than one week, RNAi peanut seeds for presence of transgene and for a no-aflatoxin accumulation trait, using only few seeds.

<table border="0" cellpadding="0" cellspacing="0" width="597">
	<tbody>
		<tr height="40">
			<td height="40" style="height:40px;width:256px;">Primers, oligonucleotides</td>
			<td style="width:127px;">DNA Technologies, Coralville, IA, USA</td>
			<td style="width:123px;">n/a</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:256px;">Dneasy Plant Mini Kit</td>
			<td style="width:127px;">Qiagen, Valencia, CA</td>
			<td style="width:123px;">69106</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="64">
			<td height="64" style="height:64px;width:256px;">Czapek Dox agar medium</td>
			<td style="width:127px;">Oxoid, by Thermo Fisher Scientific, Waltham, MA</td>
			<td style="width:123px;">CM0095</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:256px;">Agar</td>
			<td style="width:127px;">Thermo Fisher Scientific, Waltham, MA</td>
			<td style="width:123px;">BP 1423</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:256px;">Freezer -80&#176;C</td>
			<td style="width:127px;">n/a</td>
			<td style="width:123px;">n/a</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="32">
			<td height="32" style="height:32px;width:256px;">Aluminum Oxide, Al2O3</td>
			<td style="width:127px;">Fisher Scientific</td>
			<td style="width:123px;">A941</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="39">
			<td height="39" style="height:39px;width:256px;">SPE Reservoirs 1.5 mL</td>
			<td style="width:127px;">Grace Davison Discovery Scientific</td>
			<td style="width:123px;">210011</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:256px;">Frits for 1.5 mL SPE reservoir</td>
			<td style="width:127px;">Grace Davison Discovery Scientific</td>
			<td style="width:123px;">211401</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:256px;">Autosampler vials</td>
			<td style="width:127px;">Waters Corporation, Milford, MA</td>
			<td style="width:123px;">186005221</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="150">
			<td height="150" style="height:150px;width:256px;">Waters Acquity Ultra-Performance Liquid-Chromatography (UPLC) instrument; UPLC-H-Class Quaternary Solvent Manager; UPLC Sample Manager; UPLC Fluorescent detector (FLR); UPLC BEH C18 2.1mmx50mm, 1.7mm column</td>
			<td style="width:127px;">Waters Corporation, Milford, MA</td>
			<td style="width:123px;"></td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="66">
			<td height="66" style="height:66px;width:256px;">Finnigan LCQ Advantage MAX ion trap mass spectrometer, with Xcalibur version 1.4 software</td>
			<td style="width:127px;">Thermo Electron Corp., San Jose, CA</td>
			<td style="width:123px;"></td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:256px;">Aflatoxin standards, B1, B2, G1 and G2</td>
			<td style="width:127px;">Sigma-Aldrich, St. Louis, MO</td>
			<td style="width:123px;">A6636; A9887; A0138; A0263</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:256px;">Systat Software 12.2</td>
			<td style="width:127px;">SYSTAT Software Inc., Point Richmond, CA</td>
			<td style="width:123px;"></td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="32">
			<td height="32" style="height:32px;width:256px;">Trizol reagent</td>
			<td style="width:127px;">Invitrogen, CA</td>
			<td style="width:123px;">15596-018</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:256px;">SuperScript III First Strand Synthesis Super Mix</td>
			<td style="width:127px;">Invitrogen, CA</td>
			<td style="width:123px;">11752-050</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="45">
			<td height="45" style="height:45px;width:256px;">ABI 7500 Real-Time PCR</td>
			<td style="width:127px;">Lifetechnologies, Grand Island, NY</td>
			<td style="width:123px;">4406984</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="32">
			<td height="32" style="height:32px;width:256px;">Luria Broth-Miller</td>
			<td style="width:127px;">Fisher Scientific</td>
			<td style="width:123px;">R453642</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="32">
			<td height="32" style="height:32px;width:256px;">pENTR1A</td>
			<td style="width:127px;">Invitrogen, CA</td>
			<td style="width:123px;">A10462</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="32">
			<td height="32" style="height:32px;width:256px;">LR Clonase II enzyme mix</td>
			<td style="width:127px;">Invitrogen, CA</td>
			<td style="width:123px;">11791-020</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="32">
			<td height="32" style="height:32px;width:256px;">T4 DNA Ligase</td>
			<td style="width:127px;">NEB Biolabs</td>
			<td style="width:123px;">M0202L</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:256px;">Gelrite</td>
			<td style="width:127px;">Sigma-Aldrich, St. Louis, MO</td>
			<td style="width:123px;">G1919</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:256px;">Acetosyringone</td>
			<td style="width:127px;">Sigma-Aldrich, St. Louis, MO</td>
			<td style="width:123px;">D134406</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="38">
			<td height="38" style="height:38px;width:256px;">QIAcube robot workstation</td>
			<td style="width:127px;">Qiagen, Valencia, CA</td>
			<td style="width:123px;">9001292</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="83">
			<td height="83" style="height:83px;width:256px;">Antibiotics: kanamycin, cefotaxime, gentamicin; streptomycin</td>
			<td style="width:127px;">Goldbio, St. Louis, MO</td>
			<td style="width:123px;">cef.: C-104-25; kan: K-120-5; gent.: G-400-1; strep.: S-150-50</td>
			<td style="width:92px;"></td>
		</tr>
		<tr height="46">
			<td height="46" style="height:46px;width:256px;">Platinum Taq DNA Polymerase High Fidelity</td>
			<td style="width:127px;">Invitrogen, CA</td>
			<td style="width:123px;">11304-029</td>
			<td style="width:92px;"></td>
		</tr>
	</tbody>
</table>

rnai-mediated control of aflatoxins in peanut: method to analyze mycotoxin production and transgene expression in the peanut/aspergillus pathosystem

The Food and Agriculture Organization of the United Nations estimates that 25% of the food crops in the world are contaminated with aflatoxins. That represents 100 million tons of food being destroyed or diverted to non-human consumption each year. Aflatoxins are powerful carcinogens normally accumulated by the fungi Aspergillus flavus and A. parasiticus in cereals, nuts, root crops and other agricultural products. Silencing of five aflatoxin-synthesis genes by RNA interference (RNAi) in peanut plants was used to control aflatoxin accumulation following inoculation with A. flavus. Previously, no method existed to analyze the effectiveness of RNAi in individual peanut transgenic events, as these usually produce few seeds, and traditional methods of large field experiments under aflatoxin-conducive conditions were not an option. In the field, the probability of finding naturally contaminated seeds is often 1/100 to 1/1,000. In addition, aflatoxin contamination is not uniformly distributed. Our method uses few seeds per transgenic event, with small pieces processed for real-time PCR (RT-PCR) or small RNA sequencing, and for analysis of aflatoxin accumulation by ultra-performance liquid chromatography (UPLC). RNAi-expressing peanut lines 288-72 and 288-74, showed up to 100% reduction (p&#8804;0.01) in aflatoxin B1 and B2 compared to the control that accumulated up to 14,000 ng.g-1 of aflatoxin B1 when inoculated with aflatoxigenic A. flavus. As reference, the maximum total of aflatoxins allowable for human consumption in the United States is 20 ng.g-1. This protocol describes the application of RNAi-mediated control of aflatoxins in transgenic peanut seeds and methods for its evaluation. We believe that its application in breeding of peanut and other crops will bring rapid advancement in this important area of science, medicine and human nutrition, and will significantly contribute to the international effort to control aflatoxins, and potentially other mycotoxins in major food crops.

Plasmid p5XCAPD was made as a derivative of pCAPD 29, and used it to transform peanut plants; this vector carries inverted repeats of five small fragments, 70-80 bp each, of aflatoxin-synthesis genes of A. flavus separated by an intron (Figure 1). Fragments of AFL2G_07224 (aflR), AFL2G_07223 (aflS or aflJ), AFL2G_05027 (aflatoxin efflux pump, aflep), AFL2G_07228 (aflC/pksA/pksL1), and AFL2G_07731 (pes1) were used for the construct, numbers on Figure 1 correspond to A. flavus genome annotation in BROAD Institute, Cambridge, MA, and the literature 42. A total of 99 peanut lines were regenerated after going through the transformation process, 50 were PCR positive for NPTII detected by STN-PCR, and 33 lines were PCR positive and produced seeds. Only seven PCR positive lines were clonally propagated and tested by the present method for aflatoxin accumulation, all seven showed between 60% and 100% less aflatoxin accumulation than the control. Here we show results of two of those seven lines. As individual transgenic events usually produce few seeds, a method was developed to use a minimum number of seeds while still being able to do parametric statistical analysis. A flowchart of the sample preparation and experimental setup is shown in Figure 5 and Table 1. Though the first generation of transgenic seeds is typically hemizygous, it is expected that the cell-to-cell and systemic movement of small interfering RNA (siRNA) generated through RNA interference should confer aflatoxin-synthesis silencing throughout the plant.
<img alt="Figure 5" src="/files/ftp_upload/53398/53398fig5.jpg" /> 
Figure 5. Schematic flowchart of the method to analyze effectiveness of RNAi in silencing Aspergillus aflatoxin-synthesis genes in peanut seeds. Graphic representation of the work flow when processing peanut samples for gene expression or aflatoxin analysis. <a href="https://www.jove.com/files/ftp_upload/53398/53398fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
RNAi peanut lines 288-72 and 288-74 showed presence of the NPTII selectable maker when tested by STN-PCR, gel sections are shown in Figure 6 (top), original pictures are available from the authors upon request. Plasmid pCAPD was not used as a control of transformation since it encodes inverted repeats of two genes Cmr (chloramphenicol resistance) and CcdB (toxin) of unknown effect on plants. PCR negative peanut line 288-9 and others which went through the regeneration process and was grown in the same conditions as RNAi lines, were used as negative control.
<img alt="Figure 6" src="/files/ftp_upload/53398/53398fig6.jpg" /> 
Figure 6. Detection of transgenics and Real Time expression of RNAi insert. Top: Single-tube, Nested PCR detection of transgenic peanut lines RNAi-288-72 and RNAi-288-74, positive plants. Controls: W (water), PP (positive plant), MM (master mix), p (plasmid p5XCAPD); fractions 1/2&#160; 1/4 1/8 1/16 represent 2-fold dilutions of DNA. Bottom: Real-Time PCR detection of expression of the RNAi insert (primer sets: RT_5X_1, RT_5X_2, as in Figure 1, on immature (yellow) and mature (brown) cotyledons of transgenic lines at 24 and 48hr incubation; gray line: CT = 1. Histograms represent the means and standard error bars (T) of three biological samples with three technical replicates. The relative quantification of RNAi insert was normalized with respect to the housekeeping gene Actin as an internal control and comparative fold expression of the transgene calculated as described in 5.2.2 and 5.3. <a href="https://www.jove.com/files/ftp_upload/53398/53398fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
To test the effectiveness of plant-host RNAi-mediated potential control of aflatoxin accumulation, freshly harvested conidia of Aspergillus flavus NRRL 3357 were applied on the cut surface of half cotyledons from which the embryos and testa had been removed (Figures 3, 4). A. flavus NRRL 3357, for which the genome has been sequenced and was the basis for designing p5XCAPD, was kindly provided by Dr. Horn at USDA-ARS-NPRL. The resulting fungal invasion of half cotyledon after 24, 48 and 72 hr at 30 &#176;C is shown in Figure 4. Samples of inoculated half cotyledons were collected at 24, 48, 72, 96 hr of incubation, and analyzed for the main four aflatoxins B1, B2, G1 and G2 using UPLC and confirmed by LC-MS; results are shown in Figure 6. Aflatoxin concentrations were determined using a published method with modifications 36. At 96 hr incubation, cotyledons start to disintegrate because of the fungal infection. RNAi line 288-72 exhibited significantly lower levels of aflatoxins than the control at all sampling dates in immature cotyledons and at most sampling dates in the mature ones. RNAi line 288-74 showed significantly lower levels of aflatoxins at most sampling dates. Levels of significance of Tukey&#39;s test are indicated with asterisks in the graphic of Figure 7.
<img alt="Figure 7" src="/files/ftp_upload/53398/53398fig7.jpg" /> 
Figure 7. Aflatoxins B1 and B2 in half peanut cotyledons after incubation (24, 48, 72 and 96 hr) with Aspergillus flavus. Control: seeds of 288-9 non-transgenic line; RNAi: seeds from RNAi-288-72 and RNAi-288-74, transgenic for RNAi p5XCAPD to silence five aflatoxin-synthesis genes. (A) Aflatoxin B1 in mature seeds (brown); (B) Aflatoxin B2 mature seeds; (C) Aflatoxin B1 in immature seeds (yellow) and (D) Aflatoxin B2 in immature seeds. Mean values with the corresponding standard error bars (T) of duplicate biological samples are represented. Statistically significant differences Tukey&#39;s test *: p &#8804; 0.05, **: p &#8804; 0.01, ***: p &#8804; 0.001. <a href="https://www.jove.com/files/ftp_upload/53398/53398fig7large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Overall, RNAi-288-72 showed throughout the experiment (24 to 96 hr incubation), a 94%-100% reduction in aflatoxin B2, and a 90%-100% reduction in aflatoxin B1 compared to the control. RNAi-288-74 showed a 63%-100% reduction in aflatoxin B2 and 60%-100% reduction in aflatoxin B1, Figure 7.
Primers used for Real-Time PCR detection of expression of the RNAi insert are shown in Figure 1. Peanut-seed cotyledons were analyzed without embryos, to remove their natural defenses and be able to detect the potential effect of RNAi on the area most exposed to fungal invasion, the cotyledons. Expression of the RNAi insert detected in immature cotyledons (yellow) of line 288-74 by primer set RT_5X_1 was four fold over the CT=1 threshold of the negative control, and by primer set RT_5X_2 was 19 fold above the threshold, all at 24 hr incubation. At least three out of five consecutive gene fragments used in the peanut transformation, 5027, 7223 and 7228 (aflep, aflS/aflJ, and aflC/pksA, respectively) were detected by RT-PCR (Figure 1, 6). Expression of RNAi insert was not detected in mature cotyledons at 24 hr, or on mature or immature cotyledons at 48 hr incubation, Figure 6 (bottom).
<table fo:keep-together.within-page="1">
	<tbody>
		<tr height="21">
			<td height="65" rowspan="3" style="height:65px;width:64px;">Peanut Line</td>
			<td rowspan="3" style="width:64px;">Time of sampling</td>
			<td colspan="3" style="width:192px;">Samples for RT-PCR</td>
			<td colspan="3" rowspan="2" style="width:192px;">Samples for aflatoxin analysis (inoculated)</td>
			<td rowspan="3" style="width:64px;">Number of seeds</td>
		</tr>
		<tr height="22">
			<td colspan="3" height="22" style="height:22px;width:192px;">(non inoculated)</td>
		</tr>
		<tr height="22">
			<td height="22" style="height:22px;width:64px;">Rep 1</td>
			<td style="width:64px;">Rep 2</td>
			<td style="width:64px;">Rep 3</td>
			<td style="width:64px;">Rep 1</td>
			<td style="width:64px;">Rep 2</td>
			<td style="width:64px;">Rep 3</td>
		</tr>
		<tr height="22">
			<td height="66" rowspan="3" style="height:66px;width:64px;">RNAi (yellow)</td>
			<td style="width:64px;">24 hr</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td rowspan="3" style="width:64px;">4.5</td>
		</tr>
		<tr height="22">
			<td height="22" style="height:22px;width:64px;">48 hr</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
		</tr>
		<tr height="22">
			<td height="22" style="height:22px;width:64px;">72 hr</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
		</tr>
		<tr height="22">
			<td height="22" style="height:22px;width:64px;">Control</td>
			<td style="width:64px;">24 hr</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td rowspan="3" style="width:64px;">4.5</td>
		</tr>
		<tr height="22">
			<td height="22" style="height:22px;width:64px;">(yellow)</td>
			<td style="width:64px;">48 hr</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
		</tr>
		<tr height="22">
			<td height="22" style="height:22px;width:64px;"></td>
			<td style="width:64px;">72 hr</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
			<td style="width:64px;">1</td>
		</tr>
	</tbody>
</table>
Table 2. Example of small-sample setup to analyze gene expression and aflatoxin accumulation in RNAi peanut seeds. Complete analysis of expression and aflatoxins for one maturity group (i.e., yellow), with three sampling times (24, 48 and 72 hr), in triplicate, would require 4.5 seeds, each number one in the table represents half cotyledon.

Watch this Scientific Journal Video about RNAi-mediated Control of Aflatoxins in Peanut: Method to Analyze Mycotoxin Production and Transgene Expression in the Peanut/Aspergillus Pathosystem at JoVE.c

RNAi-mediated Control of Aflatoxins in Peanut: Method to Analyze Mycotoxin Production and Transgene Expression in the Peanut/Aspergillus Pathosystem

We demonstrate a method for the analysis of aflatoxins and transgene expression in peanut seeds that contain RNA-interference signals for silencing aflatoxin-synthesis genes in the fungus Aspergillus flavus. RNAi-mediated control of mycotoxins in plants has not been reported previously.

RNAi-mediated Control of Aflatoxins in Peanut: Method to Analyze Mycotoxin Production and Transgene Expression in the Peanut/Aspergillus Pathosystem

The Food and Agriculture Organization of the United Nations estimates that 25% of the food crops in the world are contaminated with aflatoxins. That ...

rnai-mediated-control-aflatoxins-peanut-method-to-analyze-mycotoxin

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Environment

Optimize Flue Gas Settings to Promote Microalgae Growth in Photobioreactors via Computer Simulations

Flue gas from power plants can promote algal cultivation and reduce greenhouse gas emissions1. Microalgae not only capture solar energy more efficiently than plants3, but also synthesize advanced biofuels2-4. Generally, atmospheric CO2 is not a sufficient source for supporting maximal algal growth5. On the other hand, the high concentrations of CO2 in industrial exhaust gases have adverse effects on algal physiology. Consequently, both cultivation conditions (such as nutrients and light) and the control of the flue gas flow into the photo-bioreactors are important to develop an efficient &ldquo;flue gas to algae&rdquo; system. Researchers have proposed different photobioreactor configurations4,6 and cultivation strategies7,8 with flue gas. Here, we present a protocol that demonstrates how to use models to predict the microalgal growth in response to flue gas settings. We perform both experimental illustration and model simulations to determine the favorable conditions for algal growth with flue gas. We develop a Monod-based model coupled with mass transfer and light intensity equations to simulate the microalgal growth in a homogenous photo-bioreactor. The model simulation compares algal growth and flue gas consumptions under different flue-gas settings. The model illustrates: 1) how algal growth is influenced by different volumetric mass transfer coefficients of CO2; 2) how we can find optimal CO2 concentration for algal growth via the dynamic optimization approach (DOA); 3) how we can design a rectangular on-off flue gas pulse to promote algal biomass growth and to reduce the usage of flue gas. On the experimental side, we present a protocol for growing Chlorella under the flue gas (generated by natural gas combustion). The experimental results qualitatively validate the model predictions that the high frequency flue gas pulses can significantly improve algal cultivation.

Flue gas from power plants is a cheap CO2 source for algal growth. We have built prototype &#34;flue gas to algal cultivation&#34; systems and described how to scale up the algal cultivation process. We have demonstrated the use of a mass-transfer bio-reaction model to simulate and to design the optimal operation of flue gas for the growth of Chlorella sp. in algal photo-bioreactors.

Flue gas from power plants can promote algal cultivation and reduce greenhouse gas emissions1. Microalgae not only capture solar energy more efficiently ...

Extraction and Analysis of Microbial Phospholipid Fatty Acids in Soils

Phospholipid fatty acids (PLFAs) are key components of microbial cell membranes. The analysis of PLFAs extracted from soils can provide information about the overall structure of terrestrial microbial communities. PLFA profiling has been extensively used in a range of ecosystems as a biological index of overall soil quality, and as a quantitative indicator of soil response to land management and other environmental stressors.
The standard method presented here outlines four key steps: 1. lipid extraction from soil samples with a single-phase chloroform mixture, 2. fractionation using solid phase extraction columns to isolate phospholipids from other extracted lipids, 3. methanolysis of phospholipids to produce fatty acid methyl esters (FAMEs), and 4. FAME analysis by capillary gas chromatography using a flame ionization detector (GC-FID). Two standards are used, including 1,2-dinonadecanoyl-sn-glycero-3-phosphocholine (PC(19:0/19:0)) to assess the overall recovery of the extraction method, and methyl decanoate (MeC10:0) as an internal standard (ISTD) for the GC analysis.

Phospholipid fatty acids provide information about the structure of soil microbial communities. We present methods for extraction from soil samples with a single-phase chloroform mixture, fractionation of extracted lipids using solid phase extraction columns, and methanolysis to produce fatty acid methyl esters, which are analyzed by capillary gas chromatography.

Phospholipid fatty acids (PLFAs) are key components of microbial cell membranes. The analysis of PLFAs extracted from soils can provide information about ...

A Gusseted Thermogradient Table to Control Soil Temperatures for Evaluating Plant Growth and Monitoring Soil Processes

Thermogradient tables were first developed in the 1950s primarily to test seed germination over a range of temperatures simultaneously without using a series of incubators. A temperature gradient is passively established across the surface of the table between the heated and cooled ends and is lost quickly at distances above the surface. Since temperature is only controlled on the table surface, experiments are restricted to shallow containers, such as Petri dishes, placed on the table. Welding continuous aluminum vertical strips or gussets perpendicular to the surface of a table enables temperature control in depth via convective heat flow. Soil in the channels between gussets was maintained across a gradient of temperatures allowing a greater diversity of experimentation. The gusseted design was evaluated by germinating oat, lettuce, tomato, and melon seeds. Soil temperatures were monitored using individual, battery-powered dataloggers positioned across the table. LED lights installed in the lids or along the sides of the gradient table create a controlled temperature chamber where seedlings can be grown over a range of temperatures. The gusseted design enabled accurate determination of optimum temperatures for fastest germination rate and the highest percentage germination for each species. Germination information from gradient table experiments can help predict seed germination and seedling growth under the adverse soil conditions often encountered during field crop production. Temperature effects on seed germination, seedling growth, and soil ecology can be tested under controlled conditions in a laboratory using a gusseted thermogradient table.

Traditional thermogradient tables create a range of temperatures across the surface. Welding gussets perpendicular to the surface of a thermogradient table will control temperature in depth increasing possible research applications.

Thermogradient tables were first developed in the 1950s primarily to test seed germination over a range of temperatures simultaneously without using a ...

Production and Measurement of Organic Particulate Matter in the Harvard Environmental Chamber

The production and the evolution of atmospheric organic particulate matter (PM) are insufficiently understood for accurate simulations of atmospheric chemistry and climate. The complex production mechanisms and reaction pathways make this a challenging research topic. To address these issues, an environmental chamber, providing enough residence time and close-to-ambient concentrations of precursors for secondary organic materials, is needed. The Harvard Environmental Chamber (HEC) was built to serve this need, simulating the production of gas and particle phase species from volatile organic compounds (VOCs). The HEC has a volume of 4.7 m3 and a mean residence time of 3.4 h under typical operating conditions. It is operated as a completely mixed flow reactor (CMFR), providing the possibility of indefinite steady-state operation across days for sample collection and data analysis. The operation procedures are described in detail in this article. Several types of instrumentation are used to characterize the produced gas and particles. A High-Resolution Time-of-Fight Aerosol Mass Spectrometer (HR-ToF-AMS) is used to characterize particles. A Proton-Transfer-Reaction Mass Spectrometer (PTR-MS) is used for gaseous analysis. Example results are presented to show the use of the environmental chamber in a wide variety of applications related to the physicochemical properties and reaction mechanisms of organic atmospheric particulate matter.

This paper describes operation procedures for the Harvard Environmental Chamber (HEC) and related instrumentation for measuring gaseous and particle species. The environmental chamber is used to produce and study secondary organic species produced from the organic precursors, especially related to atmospheric organic particulate matter.

The production and the evolution of atmospheric organic particulate matter (PM) are insufficiently understood for accurate simulations of atmospheric ...

Procedures of Laboratory Fumigation for Pest Control with Nitric Oxide Gas

Nitric oxide (NO) is a newly discovered fumigant for postharvest pest control. This paper provides detailed protocols for conducting NO fumigation on fresh products and procedures for residue analysis and product quality evaluation. An airtight fumigation chamber containing fresh fruit and vegetables is first flushed with nitrogen (N2) to establish an ultralow oxygen (ULO) environment followed by injection of NO. The fumigation chamber is then kept at a low temperature of 2 - 5 &#176;C for a specified time period necessary to kill a target pest to complete a fumigation treatment. At the end of a fumigation treatment, the fumigation chamber is flushed with N2 to dilute NO prior to opening the chamber to ambient air to prevent the reaction between NO and O2, which produces NO2 and may damage delicate fresh products. At different times after NO fumigation, NO2 in headspace and nitrate and nitrite in liquid samples were measured as residues. Product quality was evaluated after 2 weeks of post-treatment cold storage to determine effects of NO fumigation on product quality. Keeping&#160;O2 from reacting with NO is critical to NO fumigation and is an important part of the protocols. Measuring NO levels is challenging and a practical solution is provided. Possible protocol modifications are also suggested for measuring NO levels in the fumigation chambers as well as residues. NO fumigation has the potential to be a practical alternative to methyl bromide fumigation for postharvest pest control on fresh and stored products. This publication is intended to assist other researchers in conducting NO fumigation research for postharvest pest control and accelerating the development of NO fumigation for practical applications.

This paper describes nitric oxide (NO) fumigation protocols for postharvest pest control. Fumigation chambers are flushed with nitrogen (N2) to establish ultralow oxygen conditions before NO is injected. At the end, chambers are flushed with N2 to dilute NO before exposing products to ambient air to prevent exposure to NO2.

Nitric oxide (NO) is a newly discovered fumigant for postharvest pest control. This paper provides detailed protocols for conducting NO fumigation on ...

The Plant Infection Test: Spray and Wound-Mediated Inoculation with the Plant Pathogen Magnaporthe Grisea

Plants possess a powerful system to defend themselves against potential threats by pathogenic fungi. For agriculturally important plants, however, current measures to combat such pathogens have proved too conservative and, thus, not sufficiently effective, and they can potentially pose environmental risks. Therefore, it is extremely necessary to identify host-resistance factors to assist in controlling plant diseases naturally through the identification of resistant germplasm, the isolation and characterization of resistance genes, and the molecular breeding of resistant cultivars. In this regard, there is need to establish an accurate, rapid, and large-scale inoculation method to breed and develop plant resistance genes. The rice blast fungal pathogen Magnaporthe grisea causes severe disease symptoms and yield losses. Recently, M. grisea has emerged as a model organism for studying the mechanisms of plant-fungal pathogen interactions. Hence, we report the development of a plant virulence test method that is specific for M. grisea. This method provides for both spray inoculation with a conidial suspension and wounding inoculation with mycelium cubes or droplets of conidial suspension. The key step of the wounding inoculation method for detached rice leaves is to make wounds on plant leaves, which avoids any interference caused by host penetration resistance. This spray/wounding protocol contributes to the rapid, accurate, and large-scale screening of the pathotypes of M. grisea isolates. This integrated and systematic plant infection method will serve as an excellent starting point for gaining a broad perspective of issues in plant pathology.

The Plant Infection Test: Spray and Wound-Mediated Inoculation with the Plant Pathogen Magnaporthe Grisea

Here, we present a protocol to test plant virulence with the plant pathogen Magnaporthe grisea. This report will contribute to the large-scale screening of the pathotypes of fungi isolates and serve as an excellent starting point for understanding the resistant mechanisms of plants during molecular breeding.

Plants possess a powerful system to defend themselves against potential threats by pathogenic fungi. For agriculturally important plants, however, current ...

Assessing the Particulate Matter Removal Abilities of Tree Leaves

Based on the conventional cleaning methods (water cleaning (WC) + brush cleaning (BC)), this study evaluated the influence of ultrasonic cleaning (UC) on collecting various sized particulate matter (PM) retained on leaf surfaces. We further characterized the retention efficiency of leaves to various sized PM, which will help to assess the abilities of urban trees to remove PM from ambient air quantitatively. 
Taking three broadleaf tree species (Ginkgo biloba, Sophora japonica, and Salix babylonica) and two needleleaf tree species (Pinus tabuliformis and Sabina chinensis) as the research objects, leaf samples were collected 4 days (short PM retention period) and 14 days (long PM retention period) after the latest rainfall. PM retained on the leaf surfaces was collected by means of WC, BC, and UC in sequence. Then, retention efficiencies of leaves (AEleaf) to three types of the various sized PM, including easily removable PM (ERP), difficult-to-remove PM (DRP), and totally removable PM (TRP), were calculated. Only around 23%-45% of the total PM retained on leaves could be cleaned off and collected by WC. When the leaves were cleaned through WC+BC, the underestimation of the PM retention capacity of different tree species was in the range of 29%-46% for various sized PM. Almost all PM retained on leaves could be removed if UC was supplemented to WC+BC. 
In conclusion, if the UC was complemented after the conventional cleaning methods, more PM on leaf surfaces could be eluted and collected. The procedure developed in this study can be used for assessing the PM removal abilities of different tree species.

The ultrasonic cleaning method was applied to elute the particulate matter (PM) retained on leaf surfaces after PM was eluted by the conventional cleaning methods (water cleaning only or water cleaning plus brush cleaning). The methodology can help to improve the estimation accuracy for PM retention capacity of leaves.

Based on the conventional cleaning methods (water cleaning (WC) + brush cleaning (BC)), this study evaluated the influence of ultrasonic cleaning (UC) on ...

Visualizing Efficacy of Pesticides Against Disease Vector Mosquitoes in the Field

Efficacy of public health pesticides targeting nuisance and disease-vector insects such as mosquitoes, sand flies, and filth-breeding flies is not uniform across ecological zones. To best protect public and veterinary health from these insects, the environmental limitations of pesticides need to be investigated to inform effective use of the most appropriate pesticide formulations and techniques. We have developed a research program to evaluate combinations of pesticides, pesticide application equipment, and application techniques in hot-arid desert, hot-humid tropical, warm and cool temperate, and urban locations to derive pesticide use guidelines specific to target insect and environment. To these ends we designed a system of protocols to support efficient, cost-effective, portable, and standardized evaluation of a diverse range of pesticides and equipment across multiple environments. At the core of these protocols is the use of an array of small cages with colony-reared sentinel mosquitoes (adults and immatures) and sand flies (adults), strategically arranged in natural habitats and exposed to pesticide spray. Spatial and temporal patterns of pesticide efficacy are derived from percent mortality in sentinel cages, then mapped and visualized in a geographic information system. Maps of sentinel mortality data may be statistically compared to evaluate relative efficacy of a pesticide across multiple environments, or to study multiple pesticides in a single environment. Protocols may be modified to accommodate a variety of scenarios, including, for example, the vertical orientation of sentinels in canopy habitats or simultaneous testing of ground and aerial application methods.

The efficacy of public health pesticides targeting nuisance and disease-vector insects is not uniform across different ecological zones. Here we present a system of techniques using captive vector insects as sentinels for pesticide efficacy to derive electronic maps supporting the standard evaluation of pesticides across multiple environments.

Efficacy of public health pesticides targeting nuisance and disease-vector insects such as mosquitoes, sand flies, and filth-breeding flies is not uniform ...

Composition and Distribution Analysis of Bioaerosols Under Different Environmental Conditions

Variable microorganisms in particulate matter (PM) under different environmental conditions may have significant impacts on human health. In this study, we described a protocol for multiple analyses of the biological compositions in environmental PM. Five experiments are presented: (1) PM number monitoring by using a laser particle counter; (2) PM collection by using a cyclonic aerosol sampler; (3) PM collection by using a high-volume air sampler with filters; (4) culturable microbes collection by the Andersen six-stage sampler; and (5) detection of biological composition of environmental PM by bacterial 16SrDNA and fungal ITS region sequencing. We selected hazy days and a livestock farm as two typical examples of the application in this protocol. In this study, these two sampling methods, cyclonic aerosol sampler and filter sampler, showed different sampling efficiency. The cyclonic aerosol sampler performed much better in terms of collecting bacteria, while these two methods showed the same efficiency in collecting fungi. Filter samplers can work under low temperature conditions while cyclonic aerosol samplers have a sampling limitation for temperature. A solid impacting sampler, such as an Andersen six-stage sampler, can be used to sample bioaerosols directly into the culture medium, which increases the survival rate of culturable microorganisms. However, this method mainly relies on culture while more than 99% of microbes cannot be cultured. DNA extracted from the culturable bacteria collected by the Andersen six-stage sampler and samples collected by cyclonic aerosol sampler and filter sampler were detected by bacterial 16S rDNA and fungal ITS region sequencing.All the methods above may have wide application in many fields of study, such as environmental monitoring and airborne pathogen detection. From these results, we can conclude that these methods can be used under different conditions and may help other researchers further explore the health impacts of environmental bioaerosols.

Understanding the biological composition of environmental particulate matter is important for the study of its significant impacts on human health and disease spread. Here, we used three types of bioaerosol sampling methods and a biological analysis of airborne microbes to better explore airborne microbial communities under different environmental conditions.

Variable microorganisms in particulate matter (PM) under different environmental conditions may have significant impacts on human health. In this study, ...

A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant&ndash;Environment Interactions

Food security for the growing global population is a major concern. The data provided by genomic tools far exceeds the supply of phenotypic data, creating a knowledge gap. To meet the challenge of improving crops to feed the growing global population, this gap must be bridged.
Physiological traits are considered key functional traits in the context of responsiveness or sensitivity to environmental conditions. Many recently introduced high-throughput (HTP) phenotyping techniques are based on remote sensing or imaging and are capable of directly measuring morphological traits, but measure physiological parameters mainly indirectly.
This paper describes a method for direct physiological phenotyping that has several advantages for the functional phenotyping of plant&#8211;environment interactions. It helps users overcome the many challenges encountered in the use of load-cell gravimetric systems and pot experiments. The suggested techniques will enable users to distinguish between soil weight, plant weight and soil water content, providing a method for the continuous and simultaneous measurement of dynamic soil, plant and atmosphere conditions, alongside the measurement of key physiological traits. This method allows researchers to closely mimic field stress scenarios while taking into consideration the environment&#8217;s effects on the plants&#8217; physiology. This method also minimizes pot effects, which are one of the major problems in pre-field phenotyping. It includes a feed-back fertigation system that enables a truly randomized experimental design at a field-like plant density. This system detects the soil-water-content limiting threshold (&#952;) and allows for the translation of data into knowledge through the use of a real-time analytic tool and an online statistical resource. This method for the rapid and direct measurement of the physiological responses of multiple plants to a dynamic environment has great potential for use in screening for beneficial traits associated with responses to abiotic stress, in the context of pre-field breeding and crop improvement.

A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant&#8211;Environment Interactions

This high-throughput, telemetric, whole-plant water relations gravimetric phenotyping method enables direct and simultaneous real-time measurements, as well as the analysis of multiple yield-related physiological traits involved in dynamic plant&#8211;environment interactions.

Food security for the growing global population is a major concern. The data provided by genomic tools far exceeds the supply of phenotypic data, creating ...